A non-parametric method for automatic neural spike clustering based on the non-uniform distribution of the data

Journal of Neural Engineering

Volumn 8, Issue 6, 2011, Pages

  Tiganj, Z ^a   Mboup, M ^a,b  

^a INRIA   (France)

^b UNIVERSITÉ DE REIMS CHAMPAGNE ARDENNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL APPLICATION; EXTRACELLULAR RECORDING; FEATURE EXTRACTION TECHNIQUES; FIRING RATES; GREEDY ALGORITHMS; INTRACELLULAR RECORDINGS; NEAREST NEIGHBORS; NEURAL SIGNALS; NEURAL SPIKE; NON-UNIFORM DISTRIBUTION; NONPARAMETRIC METHODS; NUMBER OF CLUSTERS; PRIOR KNOWLEDGE; STATE-OF-THE-ART APPROACH; UNIFORM DISTRIBUTION; UNIMODAL;

ENZYME ACTIVITY; FEATURE EXTRACTION; NEURAL NETWORKS; SORTING;

CLUSTERING ALGORITHMS;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; HUMAN; INTRACELLULAR RECORDING; NERVE CELL MEMBRANE POTENTIAL; NERVE CONDUCTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SPIKE WAVE; ACTION POTENTIAL; BIOLOGICAL MODEL; NERVE CELL; NONPARAMETRIC TEST; PHYSIOLOGY; STATISTICAL ANALYSIS;

ACTION POTENTIALS; ALGORITHMS; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; MODELS, NEUROLOGICAL; NEURONS; STATISTICS, NONPARAMETRIC;

EID: 81855203192     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/8/6/066014     Document Type: Article

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